Embodiments of the present application relate generally to analysis of radiological images having vascular structure. Particularly, certain embodiments relate to workflow for dynamic vascular structure identification.
Clinicians may wish to analyze, survey, or diagnose a patient's circulatory system. Radiological imaging systems may provide graphical information in two-dimensional, three-dimensional, or four-dimensional corresponding to a patient's circulatory system. However, the images by themselves may not provide the clinician with a clear picture of the patient's circulatory system. In order to further assist a clinician, it may be useful to process radiological images to identify structure corresponding to a patient's circulatory system. In particular, it may be helpful to identify vascular structure in a patient.
Existing tools may be capable of identifying a patient's vascular structure. For example, General Electric Company's Advanced Vessel Analysis (AVA) may provide a package of analysis tools which aid clinicians in surgical planning, vessel disease progression and stent planning. A clinician using AVA may select a vessel for analysis. AVA may then automatically identify key aspects of the selected vessel, such as centerline of the vessel (e.g., center of vessel) and cross-section of the vessel. Analysis performed by AVA may be in a variety of formats for review, transfer, or storage.
Vascular structure identification may consume substantial processing resources. For example, a patient's vascular structure of interest may be a relatively complicated three or four dimensional shape or set of shapes. To identify an entire vascular tree of interest may consume substantial processing resources, including memory, processor availability, and processing speed, for example. In addition, vascular structure identification may also require a clinician's time.
Vascular structure identification may be an iterative process. A first try may not adequately identify vascular structure, and a clinician may need to make a series of subsequent iterations to arrive at a clinically satisfactory identification. It may be helpful for clinicians to dynamically interact with a vascular identification tool in real-time when making subsequent iterations.
Thus, there is a need for methods and systems that reduce the cost and resource consumption of vascular structure identification. Additionally, there is a need for methods and systems that improve the efficiency of vascular structure identification. Furthermore, there is a need for methods and systems that enable a user's dynamic interaction with vascular structure identification tools in real-time.